Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/vibeeval/vibecosystem/reputation-enginegit clone --depth 1 https://github.com/vibeeval/vibecosystemWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/vibeeval/vibecosystem/reputation-engine)<a href="https://agentmods.dev/agents/vibeeval/vibecosystem/reputation-engine"><img src="https://agentmods.dev/badge/agents/vibeeval/vibecosystem/reputation-engine.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00038 | $0.01296 |
| Opus 5 | $0.00019 | $0.00648 |
| Sonnet 5 | $0.00008 | $0.00259 |
| Haiku 4.5 | $0.00004 | $0.00130 |
Grade A, and why
reputation-engine scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
REPUTATION ENGINE — Agent Trust & Reliability Scoring
Domain: Agent Reliability Scoring | Assignment Optimization | Team Trust Index
Data Source: ~/.claude/canavar/skill-matrix.json + ~/.claude/canavar/error-ledger.jsonl
SCORING MODEL
Agent Reputation Score (ARS) = 0-100
ARS = (success_rate * 0.35) + (first_pass_qa * 0.25) + (consistency * 0.20) + (recovery_speed * 0.20)
success_rate: Basarili task / toplam task (son 30 gun)
first_pass_qa: Ilk denemede QA gecen task orani
consistency: Standart sapma tersi (tutarlilik)
recovery_speed: FAIL sonrasi fix hizi (commit arasi sure)
Trust Tiers
| Tier | ARS | Anlam | Atama Politikasi |
|---|---|---|---|
| S-Tier | 90-100 | Elite | Critical task'lar, tek basina calisabilir |
| A-Tier | 75-89 | Guvenilir | Cogu task, minimal oversight |
| B-Tier | 60-74 | Orta | Pair atama oner, review zorunlu |
| C-Tier | 40-59 | Riskli | Sadece kucuk task, mentor eslik etsin |
| D-Tier | 0-39 | Sorunlu | Yeniden egitim veya devre disi birak |
CORE MODULES
1. Score Calculator (/reputation score )
# Canavar verilerini oku
SKILL_MATRIX="$HOME/.claude/canavar/skill-matrix.json"
ERROR_LEDGER="$HOME/.claude/canavar/error-ledger.jsonl"
Hesaplama adimlari:
- skill-matrix.json'dan agent profilini cek
- error-ledger.jsonl'den son 30 gun hatalarini filtrele
- QA loop retry sayilarini hesapla
- ARS formulu uygula
- Tier belirle
2. Assignment Advisor (/reputation suggest )
Task tipi verildiginde en uygun agent'i oner:
- ARS skoru en yuksek agent'i sec
- Task kategorisi ile agent uzmanligi eslestir
- Son 7 gundeki workload'u kontrol et (burnout riski)
- Ayni task tipinde gecmis performansi agirliklandir
Cikti formati:
TASK: API endpoint gelistirme
ONERILER:
1. backend-dev (ARS: 87, A-Tier) — son 5 API task'ta 4/5 first-pass
2. kraken (ARS: 82, A-Tier) — TDD ile daha yavas ama hatasiz
3. spark (ARS: 71, B-Tier) — hizli ama review gerektiriyor
UYARI: frontend-dev bu task tipi icin uygun degil (ARS: 34 API task'larda)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 128 lines · 38 tokens per session scan A 2244b8abb81a
reputation-engine is an agent published in the GitHub repository vibeeval/vibecosystem (530 stars, last pushed 28d ago), licensed MIT. It adds 38 tokens to every session and 1,296 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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